{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Piecewise exponential models and creating custom models\n",
    "\n",
    "This section will be easier if we recall our three mathematical \"creatures\" and the relationships between them. First is the survival function, $S(t)$, that represents the probability of living past some time, $t$. Next is the _always non-negative and non-decreasing_ cumulative hazard function, $H(t)$. Its relation to $S(t)$ is:\n",
    "\n",
    "$$ S(t) = \\exp\\left(-H(t)\\right)$$\n",
    "\n",
    "Finally, the hazard function, $h(t)$, is the derivative of the cumulative hazard: \n",
    "\n",
    "$$h(t) = \\frac{dH(t)}{dt}$$\n",
    "\n",
    "which has the immediate relation to the survival function:\n",
    "\n",
    "$$S(t) = \\exp\\left(-\\int_{0}^t h(s) ds\\right)$$\n",
    "\n",
    "Notice that any of the three absolutely defines the other two. Some situations make it easier to define one vs the others. For example, in the Cox model, it's easist to work with the hazard, $h(t)$. In this section on parametric univariate models, it'll be easiest to work with the cumulative hazard. This is because of an asymmetry in math: derivatives are much easier to compute than integrals. So, if we define the cumulative hazard, both the hazard and survival function are much easier to reason about versus if we define the hazard and ask questions about the other two.\n",
    "\n",
    "First, let's revisit some simpler parametric models. \n",
    "\n",
    "#### The Exponential model\n",
    "\n",
    "Recall that the Exponential model has a constant hazard, that is:\n",
    "\n",
    "$$ h(t) = \\frac{1}{\\lambda} $$\n",
    "\n",
    "which implies that the cumulative hazard, $H(t)$, has a pretty simple form: $H(t) = \\frac{t}{\\lambda}$. Below we fit this model to some survival data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from lifelines.datasets import load_waltons\n",
    "waltons = load_waltons()\n",
    "T, E = waltons['T'], waltons['E']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <td>lifelines.ExponentialFitter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of observations</th>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of events observed</th>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>log-likelihood</th>\n",
       "      <td>-771.913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hypothesis</th>\n",
       "      <td>lambda_ != 1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div><table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>coef</th>\n",
       "      <th>se(coef)</th>\n",
       "      <th>coef lower 95%</th>\n",
       "      <th>coef upper 95%</th>\n",
       "      <th>z</th>\n",
       "      <th>p</th>\n",
       "      <th>-log2(p)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>lambda_</th>\n",
       "      <td>51.840</td>\n",
       "      <td>4.151</td>\n",
       "      <td>43.705</td>\n",
       "      <td>59.975</td>\n",
       "      <td>12.249</td>\n",
       "      <td>&lt;0.0005</td>\n",
       "      <td>112.180</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 263,
       "width": 608
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from lifelines import ExponentialFitter\n",
    "\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(10, 4))\n",
    "\n",
    "epf = ExponentialFitter().fit(T, E)\n",
    "epf.plot_hazard(ax=ax[0])\n",
    "epf.plot_cumulative_hazard(ax=ax[1])\n",
    "\n",
    "ax[0].set_title(\"hazard\"); ax[1].set_title(\"cumulative_hazard\")\n",
    "\n",
    "epf.print_summary(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This model does a poor job of fitting to our data. If I fit a _non-parametric_ model, like the Nelson-Aalen model, to this data, the Exponential's lack of fit is very obvious. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x126f5c630>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 316,
       "width": 474
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from lifelines import NelsonAalenFitter\n",
    "\n",
    "ax = epf.plot(figsize=(8,5))\n",
    "\n",
    "naf = NelsonAalenFitter().fit(T, E)\n",
    "ax = naf.plot(ax=ax)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It should be clear that the single parameter model is just averaging the hazards over the entire time period. In reality though, the true hazard rate exhibits some complex non-linear behaviour.\n",
    "\n",
    "#### Piecewise Exponential models\n",
    "\n",
    "What if we could break out model into different time periods, and fit an exponential model to each of those? For example, we define the hazard as:\n",
    "\n",
    "$$ \n",
    "h(t) = \\begin{cases}\n",
    "        \\lambda_0,  & \\text{if $t \\le \\tau_0$} \\\\\n",
    "        \\lambda_1 & \\text{if $\\tau_0 < t \\le \\tau_1$} \\\\\n",
    "        \\lambda_2 & \\text{if $\\tau_1 < t \\le \\tau_2$} \\\\\n",
    "        ... \n",
    "      \\end{cases}\n",
    "$$\n",
    "\n",
    "This model should be flexible enough to fit better to our dataset. \n",
    "\n",
    "The cumulative hazard is only slightly more complicated, but not too much and can still be defined in Python. In _lifelines_, univariate models are constructed such that one _only_ needs to define the cumulative hazard model with the parameters of interest, and all the hard work of fitting, creating confidence intervals, plotting, etc. is taken care. \n",
    "\n",
    "For example, _lifelines_ has implemented the `PiecewiseExponentialFitter` model. Internally, the code is a single function that defines the cumulative hazard. The user specifies where they believe the \"breaks\" are, and _lifelines_ estimates the best $\\lambda_i$. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <td>lifelines.PiecewiseExponentialFitter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of observations</th>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of events observed</th>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>log-likelihood</th>\n",
       "      <td>-647.118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hypothesis</th>\n",
       "      <td>lambda_0_ != 1, lambda_1_ != 1, lambda_2_ != 1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div><table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>coef</th>\n",
       "      <th>se(coef)</th>\n",
       "      <th>coef lower 95%</th>\n",
       "      <th>coef upper 95%</th>\n",
       "      <th>z</th>\n",
       "      <th>p</th>\n",
       "      <th>-log2(p)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>lambda_0_</th>\n",
       "      <td>162.989</td>\n",
       "      <td>27.144</td>\n",
       "      <td>109.787</td>\n",
       "      <td>216.191</td>\n",
       "      <td>5.968</td>\n",
       "      <td>&lt;0.0005</td>\n",
       "      <td>28.630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lambda_1_</th>\n",
       "      <td>31.366</td>\n",
       "      <td>4.043</td>\n",
       "      <td>23.442</td>\n",
       "      <td>39.290</td>\n",
       "      <td>7.511</td>\n",
       "      <td>&lt;0.0005</td>\n",
       "      <td>43.957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lambda_2_</th>\n",
       "      <td>4.686</td>\n",
       "      <td>0.624</td>\n",
       "      <td>3.462</td>\n",
       "      <td>5.910</td>\n",
       "      <td>5.902</td>\n",
       "      <td>&lt;0.0005</td>\n",
       "      <td>28.055</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 277,
       "width": 601
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from lifelines import PiecewiseExponentialFitter\n",
    "\n",
    "# looking at the above plot, I think there may be breaks at t=40 and t=60. \n",
    "pf = PiecewiseExponentialFitter(breakpoints=[40, 60]).fit(T, E)\n",
    "\n",
    "fig, axs = plt.subplots(nrows=1, ncols=2, figsize=(10, 4))\n",
    "\n",
    "ax = pf.plot(ax=axs[1])\n",
    "pf.plot_hazard(ax=axs[0])\n",
    "\n",
    "ax = naf.plot(ax=ax, ci_show=False)\n",
    "axs[0].set_title(\"hazard\"); axs[1].set_title(\"cumulative_hazard\")\n",
    "\n",
    "pf.print_summary(3)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see a much better fit in this model. A quantitative measure of fit is to compare the log-likelihood between exponential model and the piecewise exponential model (higher is better). The log-likelihood went from -772 to -647, respectively. We could keep going and add more and more breakpoints, but that would end up overfitting to the data. \n",
    "\n",
    "#### Univarite models in _lifelines_\n",
    "\n",
    "I mentioned that the `PiecewiseExponentialFitter` was implemented using only its cumulative hazard function. This is not a lie. _lifelines_ has very general semantics for univariate fitters. For example, this is how the entire `ExponentialFitter` is implemented:\n",
    "\n",
    "```python\n",
    "class ExponentialFitter(ParametricUnivariateFitter):\n",
    "\n",
    "    _fitted_parameter_names = [\"lambda_\"]\n",
    "\n",
    "    def _cumulative_hazard(self, params, times):\n",
    "        lambda_ = params[0]\n",
    "        return times / lambda_\n",
    "```\n",
    "\n",
    "We only need to specify the cumulative hazard function because of the 1:1:1 relationship between the cumulative hazard function and the survival function and the hazard rate. From there, _lifelines_ handles the rest. \n",
    "\n",
    "\n",
    "#### Defining our own survival models\n",
    "\n",
    "\n",
    "To show off the flexability of _lifelines_ univariate models, we'll create a brand new, never before seen, survival model. Looking at the Nelson-Aalen fit, the cumulative hazard looks looks like their might be an asymptote at $t=80$. This may correspond to an absolute upper limit of subjects' lives. Let's start with that functional form.\n",
    "\n",
    "$$ H_1(t; \\alpha) = \\frac{\\alpha}{(80 - t)} $$\n",
    "\n",
    "We subscript $1$ because we'll investigate other models. In a _lifelines_ univariate model, this is defined in the following code. \n",
    "\n",
    "**Important**: in order to compute derivatives, you must use the numpy imported from the `autograd` library. This is a thin wrapper around the original numpy. Note the `import autograd.numpy as np` below. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from lifelines.fitters import ParametricUnivariateFitter\n",
    "\n",
    "import autograd.numpy as np\n",
    "\n",
    "class InverseTimeHazardFitter(ParametricUnivariateFitter):\n",
    "    \n",
    "    # we tell the model what we want the names of the unknown parameters to be\n",
    "    _fitted_parameter_names = ['alpha_']\n",
    "\n",
    "    \n",
    "    # this is the only function we need to define. It always takes two arguments:\n",
    "    #   params: an iterable that unpacks the parameters you'll need in the order of _fitted_parameter_names\n",
    "    #   times: a vector of times that will be passed in.\n",
    "    def _cumulative_hazard(self, params, times):\n",
    "        alpha = params[0]\n",
    "        return alpha /(80 - times)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <td>lifelines.InverseTimeHazardFitter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of observations</th>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of events observed</th>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>log-likelihood</th>\n",
       "      <td>-697.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hypothesis</th>\n",
       "      <td>alpha_ != 1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div><table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>coef</th>\n",
       "      <th>se(coef)</th>\n",
       "      <th>coef lower 95%</th>\n",
       "      <th>coef upper 95%</th>\n",
       "      <th>z</th>\n",
       "      <th>p</th>\n",
       "      <th>-log2(p)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>alpha_</th>\n",
       "      <td>21.51</td>\n",
       "      <td>1.72</td>\n",
       "      <td>18.13</td>\n",
       "      <td>24.88</td>\n",
       "      <td>11.91</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>106.22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x127597198>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 316,
       "width": 474
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "itf = InverseTimeHazardFitter()\n",
    "itf.fit(T, E)\n",
    "itf.print_summary()\n",
    "\n",
    "ax = itf.plot(figsize=(8,5))\n",
    "ax = naf.plot(ax=ax, ci_show=False)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The best fit of the model to the data is:\n",
    "\n",
    "$$H_1(t) = \\frac{21.51}{80-t}$$\n",
    "\n",
    "Our choice of 80 as an asymptote was maybe mistaken, so let's allow the asymptote to be another parameter:\n",
    "\n",
    "$$ H_2(t; \\alpha, \\beta) = \\frac{\\alpha}{\\beta-t} $$\n",
    "\n",
    "If we define the model this way, we need to add a bound to the values that $\\beta$ can take. Obviously it can't be smaller than or equal to the maximum observed duration. Generally, the cumulative hazard _must be positive and non-decreasing_. Otherwise the model fit will hit convergence problems. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TwoParamInverseTimeHazardFitter(ParametricUnivariateFitter):\n",
    "    \n",
    "    _fitted_parameter_names = ['alpha_', 'beta_']\n",
    "    \n",
    "    # Sequence of (min, max) pairs for each element in x. None is used to specify no bound\n",
    "    _bounds = [(0, None), (75.0001, None)]\n",
    "    \n",
    "    def _cumulative_hazard(self, params, times):\n",
    "        alpha, beta = params\n",
    "        return alpha / (beta - times)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <td>lifelines.TwoParamInverseTimeHazardFitter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of observations</th>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of events observed</th>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>log-likelihood</th>\n",
       "      <td>-685.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hypothesis</th>\n",
       "      <td>alpha_ != 1, beta_ != 76.0001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div><table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>coef</th>\n",
       "      <th>se(coef)</th>\n",
       "      <th>coef lower 95%</th>\n",
       "      <th>coef upper 95%</th>\n",
       "      <th>z</th>\n",
       "      <th>p</th>\n",
       "      <th>-log2(p)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>alpha_</th>\n",
       "      <td>16.50</td>\n",
       "      <td>1.51</td>\n",
       "      <td>13.55</td>\n",
       "      <td>19.46</td>\n",
       "      <td>10.28</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>79.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta_</th>\n",
       "      <td>76.55</td>\n",
       "      <td>0.38</td>\n",
       "      <td>75.80</td>\n",
       "      <td>77.30</td>\n",
       "      <td>1.44</td>\n",
       "      <td>0.15</td>\n",
       "      <td>2.73</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x127247080>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 316,
       "width": 480
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "two_f = TwoParamInverseTimeHazardFitter()\n",
    "two_f.fit(T, E)\n",
    "two_f.print_summary()\n",
    "\n",
    "ax = itf.plot(ci_show=False, figsize=(8,5))\n",
    "ax = naf.plot(ax=ax, ci_show=False)\n",
    "two_f.plot(ax=ax)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the output, we see that the value of 76.55 is the suggested asymptote, that is:\n",
    "\n",
    "$$H_2(t) = \\frac{16.50} {76.55  - t}$$\n",
    "\n",
    "The curve also appears to track against the Nelson-Aalen model better too. Let's try one additional parameter, $\\gamma$, some sort of measure of decay. \n",
    "\n",
    "$$H_3(t; \\alpha, \\beta, \\gamma) = \\frac{\\alpha}{(\\beta-t)^\\gamma} $$\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from lifelines.fitters import ParametricUnivariateFitter\n",
    "\n",
    "class ThreeParamInverseTimeHazardFitter(ParametricUnivariateFitter):\n",
    "    \n",
    "    _fitted_parameter_names = ['alpha_', 'beta_', 'gamma_']\n",
    "    _bounds = [(0, None), (75.0001, None), (0, None)]\n",
    "    \n",
    "    # this is the only function we need to define. It always takes two arguments:\n",
    "    #   params: an iterable that unpacks the parameters you'll need in the order of _fitted_parameter_names\n",
    "    #   times: a numpy vector of times that will be passed in by the optimizer\n",
    "    def _cumulative_hazard(self, params, times):\n",
    "        a, b, c = params\n",
    "        return a / (b - times) ** c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <td>lifelines.ThreeParamInverseTimeHazardFitter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of observations</th>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of events observed</th>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>log-likelihood</th>\n",
       "      <td>-649.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hypothesis</th>\n",
       "      <td>alpha_ != 1, beta_ != 76.0001, gamma_ != 1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div><table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>coef</th>\n",
       "      <th>se(coef)</th>\n",
       "      <th>coef lower 95%</th>\n",
       "      <th>coef upper 95%</th>\n",
       "      <th>z</th>\n",
       "      <th>p</th>\n",
       "      <th>-log2(p)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>alpha_</th>\n",
       "      <td>1588776.28</td>\n",
       "      <td>3775137.44</td>\n",
       "      <td>-5810357.13</td>\n",
       "      <td>8987909.70</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta_</th>\n",
       "      <td>100.88</td>\n",
       "      <td>5.88</td>\n",
       "      <td>89.35</td>\n",
       "      <td>112.41</td>\n",
       "      <td>4.23</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>15.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gamma_</th>\n",
       "      <td>3.83</td>\n",
       "      <td>0.50</td>\n",
       "      <td>2.85</td>\n",
       "      <td>4.81</td>\n",
       "      <td>5.64</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>25.82</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x126aa6f60>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 316,
       "width": 480
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "three_f = ThreeParamInverseTimeHazardFitter()\n",
    "three_f.fit(T, E)\n",
    "three_f.print_summary()\n",
    "\n",
    "ax = itf.plot(ci_show=False, figsize=(8,5))\n",
    "ax = naf.plot(ax=ax, ci_show=False)\n",
    "ax = two_f.plot(ax=ax, ci_show=False)\n",
    "ax = three_f.plot(ax=ax)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our new asymptote is at $t\\approx 100, \\text{c.i.}=(87, 112)$. The model appears to fit the early times better than the previous models as well, however our $\\alpha$ parameter has more uncertainty now. Continuing to add parameters isn't advisable, as we will overfit to the data. \n",
    "\n",
    "Why fit parametric models anyways? Taking a step back, we are fitting parametric models and comparing them to the non-parametric Nelson-Aalen. Why not just always use the Nelson-Aalen model? \n",
    "\n",
    "1) Sometimes we have scientific motivations to use a parametric model. That is, using domain knowledge, we may know the system has a parametric model and we wish to fit to that model. \n",
    "\n",
    "2) In a parametric model, we are borrowing information from _all_ observations to determine the best parameters. To make this more clear, imagine taking a single observation and changing it's value wildly. The fitted parameters would change as well. On the other hand, imagine doing the same for a non-parametric model. In this case, only the local survival function or hazard function would change. Because parametric models can borrow information from all observations, and there are much _fewer_ unknowns than a non-parametric model, parametric models are said to be more _statistically efficient._ \n",
    "\n",
    "3) Extrapolation: non-parametric models are not easily extended to values outside the observed data. On the other hand, parametric models have no problem with this. However, extrapolation outside observed values is a very dangerous activity. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 465,
       "width": 427
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(3, figsize=(7, 8), sharex=True)\n",
    "\n",
    "new_timeline = np.arange(0, 85)\n",
    "\n",
    "three_f = ThreeParamInverseTimeHazardFitter().fit(T, E, timeline=new_timeline)\n",
    "\n",
    "three_f.plot_hazard(label='hazard', ax=axs[0]).legend()\n",
    "three_f.plot_cumulative_hazard(label='cumulative hazard',  ax=axs[1]).legend()\n",
    "three_f.plot_survival_function(label='survival function',  ax=axs[2]).legend()\n",
    "\n",
    "fig.subplots_adjust(hspace=0)\n",
    "# Hide x labels and tick labels for all but bottom plot.\n",
    "for ax in axs:\n",
    "    ax.label_outer()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3-parameter Weibull distribution\n",
    "\n",
    "We can easily extend the built-in Weibull model (`lifelines.WeibullFitter`) to include a new _location_ parameter:\n",
    "\n",
    "$$ H(t) = \\left(\\frac{t - \\theta}{\\lambda}\\right)^\\rho $$\n",
    "\n",
    "(When $\\theta = 0$, this is just the 2-parameter case again). In *lifelines* custom models, this looks like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "import autograd.numpy as np\n",
    "from autograd.scipy.stats import norm\n",
    "\n",
    "# I'm shifting this to exaggerate the effect \n",
    "T_ = T + 10\n",
    "\n",
    "class ThreeParameterWeibullFitter(ParametricUnivariateFitter):\n",
    "\n",
    "    _fitted_parameter_names = [\"lambda_\", \"rho_\", \"theta_\"]\n",
    "    _bounds = [(0, None), (0, None), (0, T.min()-0.001)]\n",
    "\n",
    "    def _cumulative_hazard(self, params, times):\n",
    "        lambda_, rho_, theta_ = params\n",
    "        return ((times - theta_) / lambda_) ** rho_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <td>lifelines.ThreeParameterWeibullFitter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of observations</th>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of events observed</th>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>log-likelihood</th>\n",
       "      <td>-665.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hypothesis</th>\n",
       "      <td>lambda_ != 1, rho_ != 1, theta_ != 2.9995</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div><table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>coef</th>\n",
       "      <th>se(coef)</th>\n",
       "      <th>coef lower 95%</th>\n",
       "      <th>coef upper 95%</th>\n",
       "      <th>z</th>\n",
       "      <th>p</th>\n",
       "      <th>-log2(p)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>lambda_</th>\n",
       "      <td>66.21</td>\n",
       "      <td>6.24</td>\n",
       "      <td>53.98</td>\n",
       "      <td>78.44</td>\n",
       "      <td>10.45</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>82.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rho_</th>\n",
       "      <td>4.42</td>\n",
       "      <td>0.62</td>\n",
       "      <td>3.20</td>\n",
       "      <td>5.64</td>\n",
       "      <td>5.49</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>24.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>theta_</th>\n",
       "      <td>0.00</td>\n",
       "      <td>5.92</td>\n",
       "      <td>-11.59</td>\n",
       "      <td>11.59</td>\n",
       "      <td>-0.51</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 316,
       "width": 474
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tpw = ThreeParameterWeibullFitter()\n",
    "tpw.fit(T_, E)\n",
    "tpw.print_summary()\n",
    "ax = tpw.plot_cumulative_hazard(figsize=(8,5))\n",
    "ax = NelsonAalenFitter().fit(T_, E).plot(ax=ax, ci_show=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inverse Gaussian distribution\n",
    "\n",
    "The inverse Gaussian distribution is another popular model for survival analysis. Unlike other model, it's hazard does not asympotically converge to 0, allowing for a long tail of survival. Let's model this, using the same parameterization from [Wikipedia](https://en.wikipedia.org/wiki/Inverse_Gaussian_distribution)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "from autograd.scipy.stats import norm\n",
    "\n",
    "\n",
    "class InverseGaussianFitter(ParametricUnivariateFitter):\n",
    "    _fitted_parameter_names = ['lambda_', 'mu_']\n",
    "    \n",
    "    def _cumulative_density(self, params, times):\n",
    "        mu_, lambda_ = params\n",
    "        v = norm.cdf(np.sqrt(lambda_ / times) * (times / mu_ - 1), loc=0, scale=1) + \\\n",
    "               np.exp(2 * lambda_ / mu_) * norm.cdf(-np.sqrt(lambda_ / times) * (times / mu_ + 1), loc=0, scale=1)\n",
    "        return v\n",
    "\n",
    "    def _cumulative_hazard(self, params, times):\n",
    "        return -np.log(1-np.clip(self._cumulative_density(params, times), 1e-15, 1-1e-15))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <td>lifelines.InverseGaussianFitter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of observations</th>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of events observed</th>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>log-likelihood</th>\n",
       "      <td>-724.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hypothesis</th>\n",
       "      <td>lambda_ != 1, mu_ != 1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div><table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>coef</th>\n",
       "      <th>se(coef)</th>\n",
       "      <th>coef lower 95%</th>\n",
       "      <th>coef upper 95%</th>\n",
       "      <th>z</th>\n",
       "      <th>p</th>\n",
       "      <th>-log2(p)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>lambda_</th>\n",
       "      <td>50.88</td>\n",
       "      <td>2.31</td>\n",
       "      <td>46.35</td>\n",
       "      <td>55.41</td>\n",
       "      <td>21.58</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>340.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mu_</th>\n",
       "      <td>157.46</td>\n",
       "      <td>17.76</td>\n",
       "      <td>122.66</td>\n",
       "      <td>192.26</td>\n",
       "      <td>8.81</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>59.49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 316,
       "width": 474
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "igf = InverseGaussianFitter()\n",
    "igf.fit(T, E)\n",
    "igf.print_summary()\n",
    "ax = igf.plot_cumulative_hazard(figsize=(8,5))\n",
    "ax = NelsonAalenFitter().fit(T, E).plot(ax=ax, ci_show=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Gompertz "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "class GompertzFitter(ParametricUnivariateFitter):\n",
    "    # this parameterization is slightly different than wikipedia. \n",
    "    _fitted_parameter_names = ['nu_', 'b_']\n",
    "\n",
    "    def _cumulative_hazard(self, params, times):\n",
    "        nu_, b_ = params\n",
    "        return nu_ * (np.expm1(times * b_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <td>lifelines.GompertzFitter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of observations</th>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of events observed</th>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>log-likelihood</th>\n",
       "      <td>-650.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hypothesis</th>\n",
       "      <td>nu_ != 1, b_ != 1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div><table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>coef</th>\n",
       "      <th>se(coef)</th>\n",
       "      <th>coef lower 95%</th>\n",
       "      <th>coef upper 95%</th>\n",
       "      <th>z</th>\n",
       "      <th>p</th>\n",
       "      <th>-log2(p)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>nu_</th>\n",
       "      <td>0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-234.94</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b_</th>\n",
       "      <td>0.08</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.09</td>\n",
       "      <td>-159.07</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 316,
       "width": 474
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "T, E = waltons['T'], waltons['E']\n",
    "\n",
    "ggf = GompertzFitter()\n",
    "ggf.fit(T, E)\n",
    "ggf.print_summary()\n",
    "ax = ggf.plot_cumulative_hazard(figsize=(8,5))\n",
    "ax = NelsonAalenFitter().fit(T, E).plot(ax=ax, ci_show=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### APGW\n",
    "\n",
    "From the paper, \"A Flexible Parametric Modelling Framework for Survival Analysis\", https://arxiv.org/pdf/1901.03212.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "class APGWFitter(ParametricUnivariateFitter):\n",
    "    # this parameterization is slightly different than wikipedia. \n",
    "    _fitted_parameter_names = ['kappa_', 'gamma_', 'phi_']\n",
    "\n",
    "    def _cumulative_hazard(self, params, t):\n",
    "        kappa_, phi_, gamma_ = params\n",
    "        return (kappa_ + 1) / kappa_ * ((1 + ((phi_ * t) ** gamma_) /(kappa_ + 1)) ** kappa_ -1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <td>lifelines.APGWFitter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of observations</th>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of events observed</th>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>log-likelihood</th>\n",
       "      <td>-655.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hypothesis</th>\n",
       "      <td>kappa_ != 1, gamma_ != 1, phi_ != 1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div><table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>coef</th>\n",
       "      <th>se(coef)</th>\n",
       "      <th>coef lower 95%</th>\n",
       "      <th>coef upper 95%</th>\n",
       "      <th>z</th>\n",
       "      <th>p</th>\n",
       "      <th>-log2(p)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>kappa_</th>\n",
       "      <td>19602.21</td>\n",
       "      <td>407112.67</td>\n",
       "      <td>-778323.96</td>\n",
       "      <td>817528.38</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gamma_</th>\n",
       "      <td>0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-3627.42</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>phi_</th>\n",
       "      <td>2.89</td>\n",
       "      <td>0.21</td>\n",
       "      <td>2.48</td>\n",
       "      <td>3.30</td>\n",
       "      <td>9.03</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>62.34</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 316,
       "width": 474
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "apg = APGWFitter()\n",
    "apg.fit(T, E)\n",
    "apg.print_summary(2)\n",
    "ax = apg.plot_cumulative_hazard(figsize=(8,5))\n",
    "ax = NelsonAalenFitter().fit(T, E).plot(ax=ax, ci_show=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bounded lifetimes using the beta distribution\n",
    "\n",
    "Maybe your data is bounded between 0 and some (unknown) upperbound M? That is, lifetimes can't be more than M. Maybe you know M, maybe you don't."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "n = 100\n",
    "T = 5 * np.random.random(n)**2\n",
    "T_censor = 10 * np.random.random(n)**2\n",
    "E = T < T_censor\n",
    "T_obs = np.minimum(T, T_censor)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from autograd_gamma import betainc\n",
    "\n",
    "class BetaFitter(ParametricUnivariateFitter):\n",
    "    _fitted_parameter_names = ['alpha_', 'beta_', \"m_\"]\n",
    "    _bounds = [(0, None), (0, None), (T.max(), None)]\n",
    "    \n",
    "    def _cumulative_density(self, params, times):\n",
    "        alpha_, beta_, m_ = params\n",
    "        return betainc(alpha_, beta_, times / m_)\n",
    "\n",
    "    def _cumulative_hazard(self, params, times):\n",
    "        return -np.log(1-self._cumulative_density(params, times))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/camerondavidson-pilon/code/lifelines/lifelines/fitters/__init__.py:936: StatisticalWarning: The diagonal of the variance_matrix_ has negative values. This could be a problem with BetaFitter's fit to the data.\n",
      "\n",
      "It's advisable to not trust the variances reported, and to be suspicious of the\n",
      "fitted parameters too. Perform plots of the cumulative hazard to help understand\n",
      "the latter's bias.\n",
      "\n",
      "To fix this, try specifying an `initial_point` kwarg in `fit`.\n",
      "\n",
      "  warnings.warn(warning_text, utils.StatisticalWarning)\n",
      "/Users/camerondavidson-pilon/code/lifelines/lifelines/fitters/__init__.py:460: RuntimeWarning: invalid value encountered in sqrt\n",
      "  np.einsum(\"nj,jk,nk->n\", gradient_at_times.T, self.variance_matrix_, gradient_at_times.T)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <td>lifelines.BetaFitter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of observations</th>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of events observed</th>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>log-likelihood</th>\n",
       "      <td>-79.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hypothesis</th>\n",
       "      <td>alpha_ != 1, beta_ != 1, m_ != 5.92869</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div><table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>coef</th>\n",
       "      <th>se(coef)</th>\n",
       "      <th>coef lower 95%</th>\n",
       "      <th>coef upper 95%</th>\n",
       "      <th>z</th>\n",
       "      <th>p</th>\n",
       "      <th>-log2(p)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>alpha_</th>\n",
       "      <td>0.53</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.65</td>\n",
       "      <td>-7.34</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>42.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta_</th>\n",
       "      <td>1.15</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m_</th>\n",
       "      <td>4.93</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 251,
       "width": 372
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "beta_fitter = BetaFitter().fit(T_obs, E)\n",
    "beta_fitter.plot()\n",
    "beta_fitter.print_summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Discrete survival models\n",
    "\n",
    "So far we have only been investigating continous time survival models, where times can take on any positive value. If we want to consider discrete survival times (for example, over the positive integers), we need to make a small adjustment. With discrete survival models, there is a slightly more complicated relationship between the hazard and cumulative hazard. This is because there are two ways to define the cumulative hazard. \n",
    "\n",
    "$$H_1(t) = \\sum_i^t h(t_i) $$ \n",
    "\n",
    "$$H_2(t) = -\\log(S(t))$$\n",
    "\n",
    "We also no longer have the relationship that $h(t) = \\frac{d H(t)}{dt}$, since $t$ is no longer continous. Instead, depending on which verion of the cumulative hazard you choose to use (inference will be the same), we have to redefine the hazard function in *lifelines*. \n",
    "\n",
    "$$ h(t) = H_1(t) - H_1(t-1) $$\n",
    "$$ h(t) = 1 - \\exp(H_2(t) - H_2(t+1)) $$\n",
    "\n",
    "[Here is an example](https://stats.stackexchange.com/questions/417303/what-is-the-likelihood-for-this-process) of a discrete survival model, that may not look like a survival model at first, where we use a redefined `_hazard` function.  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking for more examples of what you can build? See other unique survival models in the docs on [time-lagged survival](Modelling time-lagged conversion rates.ipynb)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
